On 9/1/2019 7:41 AM, John Levine wrote:
In article <8189de5a-3f0e-44ab-8a91-c4a41c4a404a@gulbrandsen.priv.no> you write:
Hm. How do you want to find, classify and test Python code that has been updated to support EAI, but contains no relevant code?
I ask because that's a reasonable case for Python. Python software uses third-party packages a great deal, and I have actually seen python software get EAI support merely by changing to a new version of a pip dependency. I'd think that'd apply to perl, ruby, C++, and any other language where programmers use a lot of external libraries. These days that's all of them.
Code that cleanly relies on external packages to handle EAI would be in its own category, compared to code that actively supports or limits them. For the latter, you might be able to evaluate whether the limitation is deliberate (design) or accidental (bug). The challenge might be to define a signature to scan for for the first category to determine whether its a conduit for EAI. Are there API calls that would be indicative? A./